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Hidden Markov Models For Bioinformatics

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Handbook Of Hidden Markov Models In Bioinformatics

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Author : Martin Gollery
language : en
Publisher: CRC Press
Release Date : 2008-06-12

Handbook Of Hidden Markov Models In Bioinformatics written by Martin Gollery and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-06-12 with Computers categories.

Demonstrating that many useful resources, such as databases, can benefit most bioinformatics projects, the Handbook of Hidden Markov Models in Bioinformatics focuses on how to choose and use various methods and programs available for hidden Markov models (HMMs). The book begins with discussions on key HMM and related profile methods, incl

Handbook Of Hidden Markov Models In Bioinformatics

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Author : Martin Gollery
language : en
Publisher: CRC Press
Release Date : 2008-06-12

Hidden Markov Models

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Author : David R. Westhead
language : en
Publisher: Humana
Release Date : 2017-02-22

Hidden Markov Models written by David R. Westhead and has been published by Humana this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-22 with Science categories.

This volume aims to provide a new perspective on the broader usage of Hidden Markov Models (HMMs) in biology. Hidden Markov Models: Methods and Protocols guides readers through chapters on biological systems; ranging from single biomolecule, cellular level, and to organism level and the use of HMMs in unravelling the complex mechanisms that govern these complex systems. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Hidden Markov Models: Methods and Protocols aims to demonstrate the impact of HMM in biology and inspire new research.

Inference In Hidden Markov Models

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Author : Olivier Cappé
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-04-12

Inference In Hidden Markov Models written by Olivier Cappé and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-04-12 with Mathematics categories.

This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. Topics range from filtering and smoothing of the hidden Markov chain to parameter estimation, Bayesian methods and estimation of the number of states. In a unified way the book covers both models with finite state spaces and models with continuous state spaces (also called state-space models) requiring approximate simulation-based algorithms that are also described in detail. Many examples illustrate the algorithms and theory. This book builds on recent developments to present a self-contained view.

Biological Sequence Analysis

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Author : Richard Durbin
language : en
Publisher: Cambridge University Press
Release Date : 1998-04-23

Biological Sequence Analysis written by Richard Durbin and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-04-23 with Medical categories.

Presents up-to-date computer methods for analysing DNA, RNA and protein sequences.

Probabilistic Modeling In Bioinformatics And Medical Informatics

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Author : Dirk Husmeier
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-05-06

Probabilistic Modeling In Bioinformatics And Medical Informatics written by Dirk Husmeier and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-05-06 with Computers categories.

Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following parts demonstrate how these methods are applied in bioinformatics and medical informatics. All three fields - the methodology of probabilistic modeling, bioinformatics, and medical informatics - are evolving very quickly. The text should therefore be seen as an introduction, offering both elementary tutorials as well as more advanced applications and case studies.

Data Analytics In Bioinformatics

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Author : Rabinarayan Satpathy
language : en
Publisher: John Wiley & Sons
Release Date : 2021-01-20

Data Analytics In Bioinformatics written by Rabinarayan Satpathy and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-20 with Computers categories.

Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel machine learning computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support vector machines, neural networks, and graphical models have been successful in analyzing life science data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. Machine Learning in Bioinformatics compiles recent approaches in machine learning methods and their applications in addressing contemporary problems in bioinformatics approximating classification and prediction of disease, feature selection, dimensionality reduction, gene selection and classification of microarray data and many more.

Hidden Markov Models For Bioinformatics

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Author : T. Koski
language : en
Publisher: Springer Science & Business Media
Release Date : 2001-11-30

Hidden Markov Models For Bioinformatics written by T. Koski and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-11-30 with Computers categories.

The purpose of this book is to give a thorough and systematic introduction to probabilistic modeling in bioinformatics. The book contains a mathematically strict and extensive presentation of the kind of probabilistic models that have turned out to be useful in genome analysis. Questions of parametric inference, selection between model families, and various architectures are treated. Several examples are given of known architectures (e.g., profile HMM) used in genome analysis.

Semi Markov Chains And Hidden Semi Markov Models Toward Applications

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Author : Vlad Stefan Barbu
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-01-07

Semi Markov Chains And Hidden Semi Markov Models Toward Applications written by Vlad Stefan Barbu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-01-07 with Mathematics categories.

Here is a work that adds much to the sum of our knowledge in a key area of science today. It is concerned with the estimation of discrete-time semi-Markov and hidden semi-Markov processes. A unique feature of the book is the use of discrete time, especially useful in some specific applications where the time scale is intrinsically discrete. The models presented in the book are specifically adapted to reliability studies and DNA analysis. The book is mainly intended for applied probabilists and statisticians interested in semi-Markov chains theory, reliability and DNA analysis, and for theoretical oriented reliability and bioinformatics engineers.

Bioinformatics Algorithms

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Author : Phillip Compeau
language : en
Publisher:
Release Date : 1986-06

Bioinformatics Algorithms written by Phillip Compeau and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986-06 with categories.

Bioinformatics Algorithms: an Active Learning Approach is one of the first textbooks to emerge from the recent Massive Online Open Course (MOOC) revolution. A light-hearted and analogy-filled companion to the authors' acclaimed online course (http://coursera.org/course/bioinformatics), this book presents students with a dynamic approach to learning bioinformatics. It strikes a unique balance between practical challenges in modern biology and fundamental algorithmic ideas, thus capturing the interest of students of biology and computer science students alike.Each chapter begins with a central biological question, such as "Are There Fragile Regions in the Human Genome?" or "Which DNA Patterns Play the Role of Molecular Clocks?" and then steadily develops the algorithmic sophistication required to answer this question. Hundreds of exercises are incorporated directly into the text as soon as they are needed; readers can test their knowledge through automated coding challenges on Rosalind (http://rosalind.info), an online platform for learning bioinformatics.The textbook website (http://bioinformaticsalgorithms.org) directs readers toward additional educational materials, including video lectures and PowerPoint slides.

Hidden Markov Models For Bioinformatics

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